Quantum Machine Learning Fault Injection
Marzio Vallero
Quantum Machine Learning Fault Injection.
Rel. Bartolomeo Montrucchio, Edoardo Giusto, Paolo Rech. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2022
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Abstract
This work stems from the composition of Quantum Computing, Machine Learning and Fault Injection and Reliability testing with the scope of understanding their interaction. Quantum Computing is still an emerging technology in constant evolution. The true extent of the advancements it will bring to humanity as a whole are numerous and possibly unpredictable. Machine Learning is comprised of all the techniques and attempts that aspire at infusing classical computation devices with what could be defined as "intelligence". Fault Injection and Reliability testing consists of analysis methods aimed at stressing electronic circuitry with the purpose of spotting out fault behaviours and patterns, eventually leading to the development of devices able to resist, detect and possibly correct such anomalies.
After introducing one of the current models for quantum faults induced by external radiation on transmon-based devices, a metric for reliability measurement called Quantum Vulnerability Factor (QVF) is presented in depth
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